Away from the tropical Pacific Ocean, an ENSO event is associated with
relatively minor changes of the probability distributions of atmospheric
variables. It is nonetheless important to estimate the changes accurately for
each ENSO event, because even small changes of means and variances can imply
large changes of the likelihood of extreme values. The mean signals are not
strictly symmetric with respect to El Niño and La Niña. They also
depend upon the unique aspects of the SST anomaly patterns for each event. As
for changes of variance and higher moments, little is known at present. This is
a concern especially for precipitation, whose distribution is strongly skewed
in areas of mean tropospheric descent.

These issues are examined here in observations and GCM simulations of the
northern winter (January-March, JFM). For the observational analysis, the 42-yr
(1958-99) reanalysis data generated at NCEP are stratified into neutral, El
Niño, and La Niña winters. The GCM analysis is based on NCEP
atmospheric GCM runs made with prescribed seasonally evolving SSTs for neutral,
warm, and cold ENSO conditions. A large number (180) of seasonal integrations,
differing only in initial atmospheric states, are made each for observed '
climatological mean JFM SSTs, the SSTs for an observed warm event (JFM 1987),
and the SSTs for an observed cold event (JFM 1989). With such a large ensemble,
the changes of probability even in regions not usually associated with strong
ENSO signals are ascertained.

The results suggest a substantial asymmetry in the remote response to El
Niño and La Niña, not only in the mean but also the variability.
In general the remote seasonal mean geopotential height response in the El
Niño experiment is stronger, but also more variable, than in the
La Niña experiment. One implication of this result is that seasonal
extratropical anomalies may not necessarily be more predictable during El
Niño than La Niña. The stronger seasonal extratropical
variability during El Niño is suggested to arise partly in response to
stronger variability of rainfall over the central equatorial Pacific Ocean. The
changes of extratropical variability in these experiments are large enough to
affect substantially the risks of extreme seasonal anomalies in many regions.
These and other results confirm that the remote impacts of individual tropical
ENSO events can deviate substantially from historical composite El Niño
and La Niña signals. They also highlight the necessity of generating
much larger GCM ensembles than has traditionally been done to estimate reliably
the changes to the full probability distribution, and especially the altered
risks of extreme anomalies, during those events.